cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
Muhammad Khoiruddin Harahap
Contact Email
choir.harahap@yahoo.com
Phone
+6282251583783
Journal Mail Official
publikasi@itscience.org
Editorial Address
Medan
Location
Unknown,
Unknown
INDONESIA
Brilliance: Research of Artificial Intelligence
Published by Information Technology and Science
ISSN : -     EISSN : 28079035     DOI : https://doi.org/10.47709
Core Subject : Science, Education,
Decision Sciences, Operations Research & Management Mathematics Other
Brilliance: Research of Artificial Intelligence is The Scientific Journal. Brilliance is published twice in one year, namely in February, May and November. Brilliance aims to promote research in the field of Informatics Engineering which focuses on publishing quality papers about the latest information about Artificial Intelligence. Submitted papers will be reviewed by the Journal and Association technical committee. All articles submitted must be original reports, previously published research results, experimental or theoretical, and colleagues will review. Articles sent to the Brilliance may not be published elsewhere. The manuscript must follow the author guidelines provided by Brilliance and must be reviewed and edited. Brilliance is published by Information Technology and Science (ITScience), a Research Institute in Medan, North Sumatra, Indonesia.
Arjuna Subject : Ilmu Komputer (semua kategori) - Aplikasi Ilmu Komputer
Articles 544 Documents
 25   26   27   28   29 
The Impact of Contextual and Emotional E-Wallet Personalization on MSME Satisfaction in Medan Christanto, Gracello Febry; Panjaitan, Erwin Setiawan
Brilliance: Research of Artificial Intelligence Vol. 5 No. 1 (2025): Brilliance: Research of Artificial Intelligence, Article Research May 2025
Publisher : Yayasan Cita Cendekiawan Al Khwarizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/brilliance.v5i1.6256

Abstract

This thesis investigates the influence of personalization features in e-wallet applications on user satisfaction among Micro, Small, and Medium Enterprises (MSMEs) in Medan City. Using the DeLone and McLean Information System Success Model (2003) as the theoretical foundation, this study highlights the importance of aligning system functions with the specific characteristics and conditions of individual users, especially within the dynamic context of MSMEs. The research introduces a novel approach to personalization by focusing on contextual and emotional dimensions, where e-wallet systems adapt to user conditions such as time of transaction, frequency of usage, and behavioral financial patterns. Unlike conventional personalization, which primarily targets content or interface, contextual-emotional personalization considers psychological nuances and daily financial habits, aiming to create a more human-centered and adaptive digital experience. The study employs a quantitative approach through the distribution of structured questionnaires to 200 MSME respondents who actively use e-wallets in their business operations. Data collected was analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) with the assistance of SmartPLS 4 software. The results demonstrate that contextual and emotional personalization has both direct and indirect effects on user satisfaction through intermediary variables such as system quality, information quality, and service quality. These findings offer practical implications for digital financial service providers aiming to improve user experience and strengthen system engagement. Additionally, the research contributes to the academic discourse by extending the DeLone and McLean model into new areas of emotional and contextual adaptability in information systems.
Comparative Analysis of MobileNetV3-Large and Small for Corn Leaf Disease Classification Maximilliano, Wesley; Rachmat, Nur
Brilliance: Research of Artificial Intelligence Vol. 5 No. 1 (2025): Brilliance: Research of Artificial Intelligence, Article Research May 2025
Publisher : Yayasan Cita Cendekiawan Al Khwarizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/brilliance.v5i1.6259

Abstract

Corn leaf disease represents a significant threat to agricultural productivity, capable of causing substantial economic losses in Indonesia. Conventional identification methods, which rely on visual observation by farmers, are frequently subjective, time-consuming, and inaccurate. This study conducts a systematic comparative analysis of two efficient Convolutional Neural Network (CNN) architecture variants, MobileNetV3-Large and MobileNetV3-Small, for the classification of four corn leaf conditions: Gray Leaf Spot, Common Rust, Northern Leaf Blight, and Healthy. The research further evaluates the influence of two prevalent optimizers, Adam and Stochastic Gradient Descent (SGD), to ascertain the most optimal model configuration through hyperparameter tuning. The models were trained and evaluated using a local image dataset from Sampang, Indonesia, comprising 4000 images. The methodology included image preprocessing, data augmentation, and hyperparameter tuning of the learning rate and batch size. The results demonstrate that both architectures achieved exceptionally high accuracy. The principal finding reveals that MobileNetV3-Small unexpectedly outperformed its larger variant, attaining a peak accuracy of 99.5% with the SGD optimizer, a learning rate of 0.01, and a batch size of 32. In comparison, MobileNetV3-Large reached a maximum accuracy of 99.0% under a similar configuration. These findings underscore the considerable potential of lightweight architectures for the development of rapid, accurate, and field-deployable plant disease diagnostic applications on mobile devices using deep learning.
Implementation Of Weighted Aggregated Sum Product Assessment (Waspas) Method In Determining English Language Learning Levels At Vanka Speaking Course Sumbawa Andini, Virna Febri; Julkarnain, M.; Yuliadi, Yuliadi
Brilliance: Research of Artificial Intelligence Vol. 4 No. 2 (2024): Brilliance: Research of Artificial Intelligence, Article Research November 2024
Publisher : Yayasan Cita Cendekiawan Al Khwarizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/brilliance.v4i2.4207

Abstract

English is an international language that plays a crucial role in global communication. English is very influential in aspects of life, ranging from the work sector to the education sector. Vanka Speaking Course Sumbawa is one of the course institutions in Sumbawa Regency that accepts participants from various levels, namely elementary to junior high school, with multiple levels and six levels of learning. Currently, Vanka Speaking Course Sumbawa has seven tutors with 142 students divided into 13 regular classes (117 people) and 12 private classes (25 people). In a language course like this, determining the student's learning level is a critical initial stage. This allows teachers to design learning programs with suitable modules and materials to meet the needs of each student. The course party still needs help determining the initial stage and learning level that suits the student's abilities. This study aims to apply the Weighted Aggregated Sum Product Assessment (WASPAS) Method in determining the level of English learning by selecting alternatives based on specific criteria. The development method designs the system using Rapid Application Development (RAD), PHP programming language, Laravel framework, MySQL database, and Unified Modeling Language (UML). After being built and tested using black box testing, this application can be run properly and help Vanka Speaking Course Sumbawa make decisions related to determining the level of English learning. The results of this study can improve the accuracy of assessment in determining the level of English learning in students and ultimately further improve the quality of learning at the Vanka Speaking Course.
Analysis of Red Brick Product Quality Improvement at UD. Batu Bata Bulan Using CRISP-DM and C4.5 Algorithm Septiana, Widya; Tsani, Farhan; Utami, Silvia Firda; Andani, Rina Meri
Brilliance: Research of Artificial Intelligence Vol. 4 No. 2 (2024): Brilliance: Research of Artificial Intelligence, Article Research November 2024
Publisher : Yayasan Cita Cendekiawan Al Khwarizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/brilliance.v4i2.4208

Abstract

UD Batu Bata Bulan is a home industry in Batu Bulan Village that produces red bricks. The industry has been operating for 20 years and has been producing bricks every day. The home industry is facing problems related to the quality of red bricks that require appropriate action to improve to meet the desired quality. In addition, the home industry is still experiencing difficulties in conducting product quality inspections due to the lack of inspection technology to help the process. The problems faced can be detrimental to UD. Batu Bata Bulan. Therefore, it is necessary to analyze the causes of defective products in the process of producing red bricks and improve the quality of red brick products. Therefore, the researcher conducted an analysis to address the problems that occurred in the company related to product quality. The solution that can be given is to classify the type of defective product using the role of data mining. In this study, the standard Cross Industry Standard Process For Data Mining (CRISP-DM) procedure and C.45 Algorithm were used in data processing.The result of this research indicate significant knowledge in classifying black color defect in data this could facilitate the quality inspection department in making accurate decisions.
Design and Construction of Traditional Tribal Musical Instruments in Sumbawa With Augmented Reality Technology Android-Based Ismiyarti, Wilia; Irawati, Irawati; Ismail, Ismail
Brilliance: Research of Artificial Intelligence Vol. 4 No. 2 (2024): Brilliance: Research of Artificial Intelligence, Article Research November 2024
Publisher : Yayasan Cita Cendekiawan Al Khwarizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/brilliance.v4i2.4210

Abstract

Areas of various tribes have distinctive characteristics, such as those of the Sumbawa tribe. Dance arts and traditional tools are elements of the Sumbawa tribal culture. Apart from dance and traditional instruments, the Sumbawa tribe has unique arts, which we generally know as fairy tales (Sakeco), accompanied by the conventional Rebana musical instrument. The culture of the Sumbawa tribe is preserved by building an art studio as a place for its preservation. Sumbawa Regency, especially in Alas District, has a studio called Kemban Alas Art Studio. We can see cultural preservation using modern technology through social media, such as Facebook, Instagram, and TikTok. However, there is still very little preservation through social media regarding Sumbawa culture, such as the content in the press itself due to the influence of new cultures, which has caused the culture of various tribes, especially the Sumbawa tribe, to be little known by most people. The method used in this research is developing the Waterfall model of LifeL Cycle (SDLC) Software and qualitative data collection. This research aims to build an Android-based Augmented Reality application at the Kemban Alas Art Studio and assist the Art Studio in educating Sumbawa tribal culture using the Augmented Reality application. The result of this research is that researchers have completed the design and development of an application that uses Android-based Aulgmelnteld Reality technology as a medium for introducing the traditional music tool Sulkul Sulmbawa.
Decision Support System For Determining Prospective Students' Department At Vocational School 1 Buer Using Simple Additive Weighting Yuliadi, Yuliadi; Romero, Reynaldo; Rodianto, Rodianto
Brilliance: Research of Artificial Intelligence Vol. 4 No. 2 (2024): Brilliance: Research of Artificial Intelligence, Article Research November 2024
Publisher : Yayasan Cita Cendekiawan Al Khwarizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/brilliance.v4i2.4211

Abstract

Choosing a major is essential for students, especially junior high school students, who must choose the appropriate field. Vocational High School (SMK) is a formal education unit that organizes vocational education at the secondary education level as a continuation of junior high school. At SMK Negeri 1 Buer, the central determination system is carried out with a ranking system where the ranking system is carried out based on the order in which prospective students register for the primary major so that it cannot be determined according to the interests and talents of the students. The purpose of this major is so that students can be directed to receive lessons based on their abilities and skills. SMK Negeri 1 Buer has eight majors: Building Modeling and Information Design, Motorcycle Engineering and Business, Visual Communication Design, Light Vehicle Engineering, Welding Engineering, Industrial Electronics Engineering, Animation, and Graphic Engineering. Therefore, this decision support system can make it easier for schools to determine majors according to students' interests and talents. This study uses the Extreme Programming method as a system development method and Simple Additive Weighting for calculating the Decision Support System, using PHP as a programming language with the Codeigniter framework and MySQL database. With this SPK, SMKN 1 Buer can distribute students according to their interests and make it easier for students to choose majors according to their interests
College Department Recommendation Expert System Web-Based Using Certainty Factor Method Hasannah, Kholifatun; Agustin, Ninik; Aziz Zein, Mochamad Taufiqurrochman Abdul
Brilliance: Research of Artificial Intelligence Vol. 4 No. 2 (2024): Brilliance: Research of Artificial Intelligence, Article Research November 2024
Publisher : Yayasan Cita Cendekiawan Al Khwarizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/brilliance.v4i2.4212

Abstract

The choice of college major is an important decision that each prospective student must take. In the decision-making process, a genuinely accurate source of information is usually needed to avoid mistakes for prospective students when determining the college major they will take. This study implemented the certainty factor method in a website-based college central recommendation expert system to minimize and avoid these mistakes. This study uses the certainty factor method to calculate the level of confidence and uncertainty of each recommendation result given by the expert system. This system will use predetermined rules to connect input and output to provide results that match the input from the user. Based on this process, prospective students will then obtain the appropriate college major recommendation results; in this study, the recommendations are based on the types of intelligence. This study aims to help solve existing problems by building an expert system to provide colleges with significant recommendations and by implementing the certainty factor method to determine the output results of recommendations from the system. This study produces a "College Major Recommendation Expert System (SIPAREK)" to help determine college majors that suit each interest to minimize the risk of mistakes in choosing a college major. In this study, the accuracy value of the recommendation results by applying the certainty factor method was 80%; from this value, it can be concluded that the certainty factor method can work well to provide recommendations for college majors in the system created.
Real Time Chicken Egg Size Classification Using Yolov4 Algorithm Sandy, Cut Lika Mestika; Husna, Asmaul; Rizal, Reyhan Achmad
Brilliance: Research of Artificial Intelligence Vol. 4 No. 2 (2024): Brilliance: Research of Artificial Intelligence, Article Research November 2024
Publisher : Yayasan Cita Cendekiawan Al Khwarizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/brilliance.v4i2.4496

Abstract

The common problem currently faced by MSMEs producing chicken eggs is experiencing difficulties in grouping egg sizes every day. Currently, grouping egg sizes is still done manually, this is less than optimal and prone to errors so that many business owners often experience losses. Grouping egg sizes before being sold is very important to note because each size affects the selling price of eggs. The use of technology on a MSME scale in laying hen farmers has not been widely adopted, this is due to limited access and understanding of technology so that to improve and strengthen productivity, management, and marketing in this business, technological innovation is needed. One alternative solution to deal with this problem is to build a real-time computerized system that can group eggs according to their size. This study aims to evaluate the performance of the Yolov4 algorithm in grouping egg sizes based on their size in real time. Based on the results of the tests carried out, the Yolov4 algorithm is able to group chicken eggs in real time with an F1-Score value: 0.89 where the F1-Score value approaching 1 indicates that the system performance has been running well. The results of this classification can be used to create a real-time egg size grouping application that can help MSMEs to monitor the productivity of chicken eggs every day.
Designing the User Interface for the Virtual Tour Selayar System using Figma Mustika, Nur; Mirfan, Mirfan; Abdul Kadir Parewe, Andi Maulidinnawati; Layuk, Tika Tandi
Brilliance: Research of Artificial Intelligence Vol. 4 No. 2 (2024): Brilliance: Research of Artificial Intelligence, Article Research November 2024
Publisher : Yayasan Cita Cendekiawan Al Khwarizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/brilliance.v4i2.4587

Abstract

This study aims to design the user interface for the Virtual Tour Selayar system using the Figma application. The system is expected to provide an interactive and informative virtual tour experience for users who wish to explore the beauty of Selayar Regency digitally. The design process employs the Design Thinking method, which consists of five main stages: understanding user needs (Empathy), defining the problem to be solved (Define), generating various ideas for potential solutions (Ideate), creating a simple version or initial model (Prototype), and testing the prototype (Tes). The Empathy stage involves observations and interviews to understand users' desires and needs concerning the virtual tour system. Next, the Define stage formulates the primary problem that the system needs to address. In the Ideate stage, various interface ideas and concepts are generated through brainstorming sessions. Subsequently, the Prototype stage produces the initial version of the interface, developed in both low fidelity and high fidelity forms using Figma. The final stage, Testing, is conducted by involving actual users to test the created prototypes. Feedback obtained from users is utilized to refine the interface, ensuring it aligns with their expectations and needs. The outcome of this research is a user interface prototype that has been tested and refined based on feedback, which is anticipated to enhance the user experience when using the Virtual Tour Selayar system effectively and satisfactorily.
Characteristics of Wireless Vibration Sensors for South Aceh Polytechnic Building Oktrison, Oktrison; Sipahutar, Erwinsyah; Jamsan, Firdaus; Candra, Rudi Arif; Ilham, Dirja Nur
Brilliance: Research of Artificial Intelligence Vol. 4 No. 2 (2024): Brilliance: Research of Artificial Intelligence, Article Research November 2024
Publisher : Yayasan Cita Cendekiawan Al Khwarizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/brilliance.v4i2.4605

Abstract

Vibration is a back-and-forth movement in a certain time interval that produces waves in a medium. Vibration can occur on a small or large scale. So on a small scale, a vibration sensor is needed to detect certain phenomena such as vibrations of engine capacity and detected pressure. On a large scale, vibration sensors can be used to detect earthquakes and other major phenomena and design a real-time vibration detection system for long distances, so vibration sensor components, controllers, and radio systems are needed. Therefore, researchers made a simple vibration detector using the experimental method. This final project aims to design, realize, and test the characteristics of the MPU 5060 accelerometer vibration sensor that is connected wirelessly. The characteristics of the sensor are tested against the magnitude of the vibration source, the distance of the vibration source, the placement medium, and the detection period. After testing the tool 10 times, it can be concluded that this simple vibration detector functions well and the highest average load results are obtained, namely in the 1-kilogram load test with a value of 1.93026 and the lowest average results are in the ceramic load test with a value of 0.651357.

Page 27 of 55 | Total Record : 544

 25   26   27   28   29 

Filter by Year

2021 2026


Reset
Filter By Issues
All Issue Vol. 6 No. 1 (2026): Brilliance: Research of Artificial Intelligence, Article Research May 2026 Vol. 5 No. 2 (2025): Brilliance: Research of Artificial Intelligence, Article Research November 2025 Vol. 5 No. 1 (2025): Brilliance: Research of Artificial Intelligence, Article Research May 2025 Vol. 4 No. 2 (2024): Brilliance: Research of Artificial Intelligence, Article Research November 2024 Vol. 4 No. 1 (2024): Brilliance: Research of Artificial Intelligence, Article Research May 2024 Vol. 3 No. 2 (2023): Brilliance: Research of Artificial Intelligence, Article Research November 2023 Vol. 3 No. 1 (2023): Brilliance: Research of Artificial Intelligence, Article Research May 2023 Vol. 2 No. 3 (2022): Brilliance: Research of Artificial Intelligence, Article Research November 2022 Vol. 2 No. 2 (2022): Brilliance: Research of Artificial Intelligence, Article Research May 2022 Vol. 2 No. 1 (2022): Brilliance: Research of Artificial Intelligence, Article Research February 2022 Vol. 1 No. 2 (2021): Brilliance: Research of Artificial Intelligence, Article Research November 2021 Vol. 1 No. 1 (2021): Brilliance: Research of Artificial Intelligence, Article Research May 2021 More Issue